Pub Date : 2024-11-12DOI: 10.1016/j.sbi.2024.102952
Judith Notbohm , Tina Perica
Since genome sequencing became accessible, determining how specific differences in genotypes lead to complex phenotypes such as disease has become one of the key goals in biomedicine. Predicting effects of sequence variants on cellular or organismal phenotype faces several challenges. First, variants simultaneously affect multiple protein properties and predicting their combined effect is complex. Second, effects of changes in a single protein propagate through the cellular network, which we only partially understand. In this review, we emphasize the importance of both biochemistry and genetics in addressing these challenges. Moreover, we highlight work that blurs the distinction between biochemistry and genetics fields to provide new insights into the genotype-to-phenotype relationships.
{"title":"Biochemistry and genetics are coming together to improve our understanding of genotype to phenotype relationships","authors":"Judith Notbohm , Tina Perica","doi":"10.1016/j.sbi.2024.102952","DOIUrl":"10.1016/j.sbi.2024.102952","url":null,"abstract":"<div><div>Since genome sequencing became accessible, determining how specific differences in genotypes lead to complex phenotypes such as disease has become one of the key goals in biomedicine. Predicting effects of sequence variants on cellular or organismal phenotype faces several challenges. First, variants simultaneously affect multiple protein properties and predicting their combined effect is complex. Second, effects of changes in a single protein propagate through the cellular network, which we only partially understand. In this review, we emphasize the importance of both biochemistry and genetics in addressing these challenges. Moreover, we highlight work that blurs the distinction between biochemistry and genetics fields to provide new insights into the genotype-to-phenotype relationships.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102952"},"PeriodicalIF":6.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-12DOI: 10.1016/j.sbi.2024.102950
Gábor Erdős, Zsuzsanna Dosztányi
Intrinsically disordered proteins (IDPs) lack a stable three-dimensional structure under physiological conditions, challenging traditional structure-based prediction methods. This review explores how modern deep learning approaches, which have revolutionized structure prediction for globular proteins, have impacted protein disorder predictions. We highlight the role of community-driven efforts in curating data and assessing state-of-the-art, which have been crucial in advancing the field. We also review state-of-the-art methods utilizing deep learning techniques, highlighting innovative approaches. We also address advancements in characterizing protein conformational ensembles directly from sequence data using novel machine learning methods.
{"title":"Deep learning for intrinsically disordered proteins: From improved predictions to deciphering conformational ensembles","authors":"Gábor Erdős, Zsuzsanna Dosztányi","doi":"10.1016/j.sbi.2024.102950","DOIUrl":"10.1016/j.sbi.2024.102950","url":null,"abstract":"<div><div>Intrinsically disordered proteins (IDPs) lack a stable three-dimensional structure under physiological conditions, challenging traditional structure-based prediction methods. This review explores how modern deep learning approaches, which have revolutionized structure prediction for globular proteins, have impacted protein disorder predictions. We highlight the role of community-driven efforts in curating data and assessing state-of-the-art, which have been crucial in advancing the field. We also review state-of-the-art methods utilizing deep learning techniques, highlighting innovative approaches. We also address advancements in characterizing protein conformational ensembles directly from sequence data using novel machine learning methods.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102950"},"PeriodicalIF":6.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-12DOI: 10.1016/j.sbi.2024.102948
Molly Davies, Maeve Boyce, Eric Conway
Core regulatory circuitry refers to the network of lineage-specific transcription factors regulating expression of both their own coding genes, and that of other transcription factors. Such autoregulatory feedback loops coordinate the transcriptome and epigenome during development and cell fate decisions. This circuitry is hijacked during oncogenesis resulting in cancer cell fate being maintained by lineage-specific transcription factors. Major advances in functional genomics and chemical biology are paving the way for a new generation of cancer therapeutics aimed at disrupting this circuitry through both direct and indirect means. Here we review these critical advances in mechanistic understanding of transcription factor addiction in cancer and how the advent of proteolysis targeting chimeras and CRISPR screen assays are leading the way for a new paradigm in targeted cancer treatments.
{"title":"Short circuit: Transcription factor addiction as a growing vulnerability in cancer","authors":"Molly Davies, Maeve Boyce, Eric Conway","doi":"10.1016/j.sbi.2024.102948","DOIUrl":"10.1016/j.sbi.2024.102948","url":null,"abstract":"<div><div>Core regulatory circuitry refers to the network of lineage-specific transcription factors regulating expression of both their own coding genes, and that of other transcription factors. Such autoregulatory feedback loops coordinate the transcriptome and epigenome during development and cell fate decisions. This circuitry is hijacked during oncogenesis resulting in cancer cell fate being maintained by lineage-specific transcription factors. Major advances in functional genomics and chemical biology are paving the way for a new generation of cancer therapeutics aimed at disrupting this circuitry through both direct and indirect means. Here we review these critical advances in mechanistic understanding of transcription factor addiction in cancer and how the advent of proteolysis targeting chimeras and CRISPR screen assays are leading the way for a new paradigm in targeted cancer treatments.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102948"},"PeriodicalIF":6.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-09DOI: 10.1016/j.sbi.2024.102949
Ainan Geng , Rohit Roy , Hashim M. Al-Hashimi
The energy cost accompanying changes in the structures of nucleic acids when they bind partner molecules is a significant but underappreciated thermodynamic contribution to binding affinity and specificity. This review highlights recent advances in measuring conformational penalties and determining their contribution to the recognition, folding, and regulatory activities of nucleic acids. Notable progress includes methods for measuring and structurally characterizing lowly populated conformational states, obtaining ensemble information in high throughput, for large macromolecular assemblies, and in complex cellular environments. Additionally, quantitative and predictive thermodynamic models have been developed that relate conformational penalties to nucleic acid-protein association and cellular activity. These studies underscore the crucial role of conformational penalties in nucleic acid recognition.
{"title":"Conformational penalties: New insights into nucleic acid recognition","authors":"Ainan Geng , Rohit Roy , Hashim M. Al-Hashimi","doi":"10.1016/j.sbi.2024.102949","DOIUrl":"10.1016/j.sbi.2024.102949","url":null,"abstract":"<div><div>The energy cost accompanying changes in the structures of nucleic acids when they bind partner molecules is a significant but underappreciated thermodynamic contribution to binding affinity and specificity. This review highlights recent advances in measuring conformational penalties and determining their contribution to the recognition, folding, and regulatory activities of nucleic acids. Notable progress includes methods for measuring and structurally characterizing lowly populated conformational states, obtaining ensemble information in high throughput, for large macromolecular assemblies, and in complex cellular environments. Additionally, quantitative and predictive thermodynamic models have been developed that relate conformational penalties to nucleic acid-protein association and cellular activity. These studies underscore the crucial role of conformational penalties in nucleic acid recognition.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102949"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-04DOI: 10.1016/j.sbi.2024.102945
Joshua Pajak , Nikolai S. Prokhorov , Paul J. Jardine , Marc C. Morais
Double-stranded DNA viruses actively package their genomes into pre-assembled protein capsids using energy derived from virus-encoded ASCE ATPase ring motors. Single molecule experiments in the aughts and early 2010s demonstrated that these motors are some of the most powerful molecular motors in nature, and that the activities of individual subunits around the ATPase ring motor are highly coordinated to ensure efficient genome encapsidation. While these studies provided a comprehensive kinetic scheme describing the events that occur during packaging, the physical basis of force generation and subunit coordination remained elusive. This article reviews recent structural and computational results that have begun to illuminate the molecular basis of force generation and DNA translocation in these powerful molecular motors.
双链DNA病毒利用病毒编码的ASCE ATPase环马达产生的能量，积极地将其基因组包装到预先组装好的蛋白囊壳中。二十世纪八十年代和二十一世纪初的单分子实验证明，这些马达是自然界中一些最强大的分子马达，ATPase 环马达周围各个亚基的活动高度协调，以确保高效的基因组封装。虽然这些研究提供了一个全面的动力学方案来描述包装过程中发生的事件，但力的产生和亚基协调的物理基础仍然难以捉摸。本文回顾了最近的结构和计算成果，这些成果已开始阐明这些强大分子马达产生作用力和 DNA 转位的分子基础。
{"title":"The mechano-chemistry of a viral genome packaging motor","authors":"Joshua Pajak , Nikolai S. Prokhorov , Paul J. Jardine , Marc C. Morais","doi":"10.1016/j.sbi.2024.102945","DOIUrl":"10.1016/j.sbi.2024.102945","url":null,"abstract":"<div><div>Double-stranded DNA viruses actively package their genomes into pre-assembled protein capsids using energy derived from virus-encoded ASCE ATPase ring motors. Single molecule experiments in the aughts and early 2010s demonstrated that these motors are some of the most powerful molecular motors in nature, and that the activities of individual subunits around the ATPase ring motor are highly coordinated to ensure efficient genome encapsidation. While these studies provided a comprehensive kinetic scheme describing the events that occur during packaging, the physical basis of force generation and subunit coordination remained elusive. This article reviews recent structural and computational results that have begun to illuminate the molecular basis of force generation and DNA translocation in these powerful molecular motors.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102945"},"PeriodicalIF":6.1,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1016/j.sbi.2024.102946
Brian C. Searle
Thermal proteome profiling (TPP) is an innovative technique that uses the principle of protein thermal stability to identify potential protein interaction partners. Employing quantitative mass spectrometry, TPP measures protein stability across the proteome, offering a comprehensive snapshot of protein interactions in a single experiment. When studying protein-protein interactions (PPI), TPP leverages changes in apparent protein melting temperatures to identify transient and weak interactions that most traditional PPI detection methodologies struggle to measure. This review discusses current TPP methodologies, the challenges of interpreting the resulting complex datasets, and opportunities to deepen and improve PPI networks. By advancing our grasp of intricate protein interactions, TPP promises to illuminate the molecular basis of diseases and drive the discovery of novel therapeutic targets.
热蛋白质组分析（TPP）是一项创新技术，它利用蛋白质热稳定性原理来识别潜在的蛋白质相互作用伙伴。TPP 采用定量质谱法测量整个蛋白质组的蛋白质稳定性，在一次实验中提供蛋白质相互作用的全面快照。在研究蛋白质-蛋白质相互作用（PPI）时，TPP 利用表观蛋白质熔解温度的变化来识别大多数传统 PPI 检测方法难以测量的瞬时弱相互作用。本综述讨论了当前的 TPP 方法、解读由此产生的复杂数据集所面临的挑战以及深化和改进 PPI 网络的机会。通过推进我们对错综复杂的蛋白质相互作用的掌握，TPP有望阐明疾病的分子基础并推动新型治疗靶点的发现。
{"title":"Characterizing protein-protein interactions with thermal proteome profiling","authors":"Brian C. Searle","doi":"10.1016/j.sbi.2024.102946","DOIUrl":"10.1016/j.sbi.2024.102946","url":null,"abstract":"<div><div>Thermal proteome profiling (TPP) is an innovative technique that uses the principle of protein thermal stability to identify potential protein interaction partners. Employing quantitative mass spectrometry, TPP measures protein stability across the proteome, offering a comprehensive snapshot of protein interactions in a single experiment. When studying protein-protein interactions (PPI), TPP leverages changes in apparent protein melting temperatures to identify transient and weak interactions that most traditional PPI detection methodologies struggle to measure. This review discusses current TPP methodologies, the challenges of interpreting the resulting complex datasets, and opportunities to deepen and improve PPI networks. By advancing our grasp of intricate protein interactions, TPP promises to illuminate the molecular basis of diseases and drive the discovery of novel therapeutic targets.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102946"},"PeriodicalIF":6.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1016/j.sbi.2024.102947
Deborah F. Kelly , Liza-Anastasia DiCecco , G.M. Jonaid , William J. Dearnaley , Michael S. Spilman , Jennifer L. Gray , Madeline J. Dressel-Dukes
{"title":"Retraction notice to “Liquid-EM goes viral – visualizing structure and dynamics” [Curr Opin Struct Biol 75 (August 2022) 102426]","authors":"Deborah F. Kelly , Liza-Anastasia DiCecco , G.M. Jonaid , William J. Dearnaley , Michael S. Spilman , Jennifer L. Gray , Madeline J. Dressel-Dukes","doi":"10.1016/j.sbi.2024.102947","DOIUrl":"10.1016/j.sbi.2024.102947","url":null,"abstract":"","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102947"},"PeriodicalIF":6.1,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.sbi.2024.102936
Kaitlyn Ledwitch , Georg Künze , Elleansar Okwei , Davide Sala , Jens Meiler
Membrane proteins remain challenging targets for conventional structural biology techniques because they need to reside within complex hydrophobic lipid environments to maintain proper structure and function. Magnetic resonance combined with site-directed spin labeling is an alternative method that provides atomic-level structural and dynamical information from effects introduced by an electron- or nuclear-based spin label. With the advent of bioorthogonal click chemistries and genetically engineered non-canonical amino acids (ncAAs), options for linking spin probes to biomolecules have substantially broadened outside the conventional cysteine-based labeling scheme. Here, we highlight current strategies to spin-label membrane proteins through ncAAs for nuclear and electron paramagnetic resonance applications. Such advances are critical for developing bioorthogonal spin labeling schemes to achieve in-cell labeling and in-cell measurements of membrane protein conformational dynamics.
{"title":"Non-canonical amino acids for site-directed spin labeling of membrane proteins","authors":"Kaitlyn Ledwitch , Georg Künze , Elleansar Okwei , Davide Sala , Jens Meiler","doi":"10.1016/j.sbi.2024.102936","DOIUrl":"10.1016/j.sbi.2024.102936","url":null,"abstract":"<div><div>Membrane proteins remain challenging targets for conventional structural biology techniques because they need to reside within complex hydrophobic lipid environments to maintain proper structure and function. Magnetic resonance combined with site-directed spin labeling is an alternative method that provides atomic-level structural and dynamical information from effects introduced by an electron- or nuclear-based spin label. With the advent of bioorthogonal click chemistries and genetically engineered non-canonical amino acids (ncAAs), options for linking spin probes to biomolecules have substantially broadened outside the conventional cysteine-based labeling scheme. Here, we highlight current strategies to spin-label membrane proteins through ncAAs for nuclear and electron paramagnetic resonance applications. Such advances are critical for developing bioorthogonal spin labeling schemes to achieve in-cell labeling and in-cell measurements of membrane protein conformational dynamics.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102936"},"PeriodicalIF":6.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142496673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.sbi.2024.102944
Jie Zhang , Xianyang Fang
RNA's inherent flexibility and dynamics pose great challenges to characterize its structure and dynamics using conventional techniques including X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and cryo-electron microscopy. Three complementary molecular ruler techniques, the electron paramagnetic resonance (EPR) spectroscopy, X-ray scattering interferometry (XSI) and Förster resonance energy transfer (FRET) which measure intramolecular and intermolecular pair-wise distance distributions in the nanometer range in a solution, have become increasingly popular and been widely used to explore RNA structure and dynamics. The prerequisites for successful application of such techniques are to achieve site-specific labeling of RNAs with spin labels, fluorescent tags, or gold nanoparticles, respectively, which are however, challenging, especially to large RNAs (generally >200 nts). Here, we briefly review the basics of these molecular rulers, how the NaM-TPT3 unnatural base pair system empower them, and their applications to explore conformational dynamics of large RNAs, especially in the context of flavivirus RNA genome.
{"title":"Empowering the molecular ruler techniques with unnatural base pair system to explore conformational dynamics of flaviviral RNAs","authors":"Jie Zhang , Xianyang Fang","doi":"10.1016/j.sbi.2024.102944","DOIUrl":"10.1016/j.sbi.2024.102944","url":null,"abstract":"<div><div>RNA's inherent flexibility and dynamics pose great challenges to characterize its structure and dynamics using conventional techniques including X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and cryo-electron microscopy. Three complementary molecular ruler techniques, the electron paramagnetic resonance (EPR) spectroscopy, X-ray scattering interferometry (XSI) and Förster resonance energy transfer (FRET) which measure intramolecular and intermolecular pair-wise distance distributions in the nanometer range in a solution, have become increasingly popular and been widely used to explore RNA structure and dynamics. The prerequisites for successful application of such techniques are to achieve site-specific labeling of RNAs with spin labels, fluorescent tags, or gold nanoparticles, respectively, which are however, challenging, especially to large RNAs (generally >200 nts). Here, we briefly review the basics of these molecular rulers, how the NaM-TPT3 unnatural base pair system empower them, and their applications to explore conformational dynamics of large RNAs, especially in the context of flavivirus RNA genome.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"89 ","pages":"Article 102944"},"PeriodicalIF":6.1,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142496672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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